A study on machine learning models for segmentation and classification of skin diseases

The most concerning factor that significantly increases semi burden in daily activities is skin disease. They are brought on by a number of things. The difficult task of classifying multiclass skin diseases is carried out mostly by visual evaluation and the addition of some clinical data. These processes, however, are labor-intensive, manual, and necessitate previous knowledge. The advancement of technology has resulted in a diversity of ML algorithms available on the market for image recognition and prediction. In this paper, different approaches for automatic segmentation and classification of certain skin diseases utilizing machine learning algorithms such as EfficientNets B0-B7, GoogLeNet Inception-v3, SVM and k-NN classifiers, etc. described in various research articles are compared and analyzed.